DocumentCode :
3315265
Title :
Cortex segmentation - a fast variational geometric approach
Author :
Goldenberg, Roman ; Kimmel, Ron ; Rivlin, Ehud ; Rudzsky, Michael
Author_Institution :
Dept. of Comput. Sci., Technion-Israel Inst. of Technol., Haifa, Israel
fYear :
2001
fDate :
2001
Firstpage :
127
Lastpage :
133
Abstract :
An automatic cortical gray matter segmentation from three-dimensional brain images (MR or CT) is a well known problem in medical image processing. We formulate it as a geometric variational problem for propagation of two coupled bounding surfaces. An efficient numerical scheme is used to implement the geodesic active surface model. Experimental results of cortex segmentation on real three-dimensional MR data are provided
Keywords :
biomedical MRI; brain; computational geometry; computerised tomography; differential geometry; image segmentation; medical image processing; variational techniques; CT images; MR images; automatic segmentation; cortex segmentation; cortical gray matter; coupled bounding surfaces; geodesic active surface model; geometric variational problem; medical image processing; three-dimensional MR data; three-dimensional brain images; Biomedical image processing; Brain modeling; Cerebral cortex; Cities and towns; Computed tomography; Computer science; Deformable models; Image segmentation; Solid modeling; World Wide Web;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Variational and Level Set Methods in Computer Vision, 2001. Proceedings. IEEE Workshop on
Conference_Location :
Vancouver, BC
Print_ISBN :
0-7695-1278-X
Type :
conf
DOI :
10.1109/VLSM.2001.938891
Filename :
938891
Link To Document :
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